1. Are institutions informed about news? T. Hendershott, D. Livdan, N. Schürhoff Discussed by: Sergey Gelman, ICEF, Higher School of Economics, Moscow The Second International Moscow Finance Conference 2012

2. Summary (I) Since Kyle (1985): the role of an informed trader is crucial – Who is informed? Mutual funds, Short sellers, Corporate insiders. – Are institutions informed? Up to now: mixed evidence, based mainly on specific news – This paper: using a very comprehensive news sample YES!

3. Summary (II) Excellent lit review A rich dataset: – returns and NYSE institutional trading data on 1667 stocks observed over 2003-2005 (756 trading days) – 126,438 days with news releases from Reuters NewsScope Sentiment Engine Results: Institutional trading predicts news arrival Institutional trading predicts news sentiment Inst. trading predicts (news) returns Inst. trading predicts earnings surprise

4. Comments (I) Causality issue: do institutions cause news or predict (have private info)? – Institutional demand drives prices (Choi, Sias 2012 RFS; Llorente et al. 2002 RFS, Baker and Warner 1993 JFE) – Institutional demand may drive news (indirect evidence: Barber et al. 2007 JFE) – Only in case of earnings surprises alternative causality stories can be majorly ruled out  Possible extension: include prediction of earnings surprise date returns  Possible extension: choose certain type of news, which can not be influenced by institutionals and returns (beside EA)

5. Comments (II) Economic significance: 10 b.p.: – small fraction of returns s.d. ≈200 b.p.  Institutions are better informed, but not “the informed” – smaller than transaction costs (average bid-ask spreads for S&P 500 stocks were 16 b.p. in 2002 -2011);  Do institutions trade on the information or just minimize their transaction costs? High persistence of institutional order imbalance: – link to theoretical models – Splitting order effect, literature on the size of informed trade (Llorente et al. 2002 RFS): Return*volume

6. Comments (III): Technical Fixed effects cause problems in all panel equations, not only VAR (use Arellano-Bover (1995)) Institutional fraction (Choi and Sias 2012 RFS) – Negative sign for volume – Institutionals seem to account for 50% to over 100% of the volume (??). Who is uninformed in the latter case? Granger causality test instead of IRF Persistence in sentiment: Effect of a news published several times in different media? Surprising: simultaneous correlations in VAR low